




from __future__ import annotations

__a							     =					[-10, -5, 0, 5, 5.1, 11, 13, 21, 3, 4, -21, -10, -5, -1, 0]
__a							     =					[-5, 0, 5, 5.1, 11, 13, 21, -1, 4, -1, -10, -5, -1, 0, -1]







def lowerCamelCase__  (     _lowercase ):

     '''simple docstring'''


     UpperCAmelCase_     :				List[Any]  =     []
     UpperCAmelCase_     :				List[str]  =     len(_lowercase )

     for i in range(_lowercase ):
          UpperCAmelCase_     :				float  =     -1
          for j in range(i + 1					,		_lowercase ):
               if arr[i] < arr[j]:
                    UpperCAmelCase_     :				Union[str, Any]  =     arr[j]
                    break
          result.append(_lowercase )
     return result







def lowerCamelCase__  (     _lowercase ):

     '''simple docstring'''


     UpperCAmelCase_     :				Union[str, Any]  =     []
     for i, outer in enumerate(_lowercase ):
          UpperCAmelCase_     :				float  =     -1
          for inner in arr[i + 1 :]:
               if outer < inner:
                    UpperCAmelCase_     :				List[Any]  =     inner
                    break
          result.append(_lowercase )
     return result







def lowerCamelCase__  (     _lowercase ):

     '''simple docstring'''


     UpperCAmelCase_     :				Optional[int]  =     len(_lowercase )
     UpperCAmelCase_     :				list[float]  =     []
     UpperCAmelCase_     :				list[float]  =     [-1] * arr_size

     for index in reversed(range(_lowercase ) ):
          if stack:
               while stack[-1] <= arr[index]:
                    stack.pop()
                    if not stack:
                         break
          if stack:
               UpperCAmelCase_     :				int  =     stack[-1]
          stack.append(arr[index] )
     return result


if __name__ == "__main__":
     from doctest import testmod
     from timeit import timeit

     testmod()
     print(next_greatest_element_slow(arr))
     print(next_greatest_element_fast(arr))
     print(next_greatest_element(arr))

     __a							     =					(
         'from __main__ import arr, next_greatest_element_slow, '
         'next_greatest_element_fast, next_greatest_element'
     )
     print(
         'next_greatest_element_slow():',
         timeit('next_greatest_element_slow(arr)', setup=setup),
     )
     print(
         'next_greatest_element_fast():',
         timeit('next_greatest_element_fast(arr)', setup=setup),
     )
     print(
         '     next_greatest_element():',
         timeit('next_greatest_element(arr)', setup=setup),
     )

from ..utils import is_flax_available, is_torch_available


if is_torch_available():
							from .autoencoder_kl import AutoencoderKL
							from .controlnet import ControlNetModel
							from .dual_transformer_ad import DualTransformeraDModel
							from .modeling_utils import ModelMixin
							from .prior_transformer import PriorTransformer
							from .ta_film_transformer import TaFilmDecoder
							from .transformer_ad import TransformeraDModel
							from .unet_ad import UNetaDModel
							from .unet_ad import UNetaDModel
							from .unet_ad_condition import UNetaDConditionModel
							from .unet_ad_condition import UNetaDConditionModel
							from .vq_model import VQModel

if is_flax_available():
							from .controlnet_flax import FlaxControlNetModel
							from .unet_ad_condition_flax import FlaxUNetaDConditionModel
							from .vae_flax import FlaxAutoencoderKL






